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A Truncated Newton Method for the Solution of Large-Scale Inequality Constrained Minimization Problems

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Abstract

A new active set Newton-type algorithm for the solution of inequality constrained minimization problems is proposed. The algorithm possesses the following favorable characteristics: (i) global convergence under mild assumptions; (ii) superlinear convergence of primal variables without strict complementarity; (iii) a Newton-type direction computed by means of a truncated conjugate gradient method. Preliminary computational results are reported to show viability of the approach in large scale problems having only a limited number of constraints.

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Authors and Affiliations

  1. Dipartimento di Informatica e Sistemistica “A. Ruberti&rdquo, Università di Roma “La Sapienza”, Via Buonarroti 12, 00185, Roma, Italy

    Francisco Facchinei, Giampaolo Liuzzi & Stefano Lucidi

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  1. Francisco Facchinei
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  2. Giampaolo Liuzzi
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  3. Stefano Lucidi
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Facchinei, F., Liuzzi, G. & Lucidi, S. A Truncated Newton Method for the Solution of Large-Scale Inequality Constrained Minimization Problems. Computational Optimization and Applications 25, 85–122 (2003). https://doi.org/10.1023/A:1022901020289

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